Active Statistics: Stories, Games, Problems, and Hands-on Demonstrations for Applied Regression and Causal Inference, Aki Vehtari, Andrew Gelman

Автор: Morgan
Название: Counterfactuals and Causal Inference
ISBN: 1107694167 ISBN-13(EAN): 9781107694163
Издательство: Cambridge Academ
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Цена: 38010.00 T
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Описание: Cause-and-effect questions are the motivation for most research in the social, demographic, and health sciences. The counterfactual approach to causal analysis represents a unified framework for the prosecution of these questions. This second edition aims to convince more social scientists to take this approach when analyzing these core empirical questions.

Автор: B. Sreenivasulu et al.
Название: Causality Tests In Econometrics: Choice of Causal Variables
ISBN: 3659504041 ISBN-13(EAN): 9783659504044
Издательство: LAP LAMBERT Academic Publishing
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Цена: 49810.00 T
Наличие на складе: Нет в наличии.
Описание: In the Present Book Chapter-I is an introductory one.Chapter-II describes the concept and causal relations by econometric models. It presents the different representations such as autoregressive, Moving – average and univariate representation of causality. Chapter-III explore lucidly the various tests for causality, we come across in econometrics. In regression analysis, researchers are interested in testing for the exogenity of variables this testing is closely related to the causality test proposed by Granger, which is explained in detail in this chapter. Chapter-IV gives the conclusions about the present study.The various relevant research articles have been presented under the title BIBLIOGRAPHY.

Автор: Imbens
Название: Causal Inference for Statistics, Social, and Biomedical Sciences
ISBN: 0521885884 ISBN-13(EAN): 9780521885881
Издательство: Cambridge Academ
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Цена: 54910.00 T
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Описание: This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.

Автор: Hooshang Nayebi
Название: Advanced Statistics for Testing Assumed Causal Relationships
ISBN: 3030547531 ISBN-13(EAN): 9783030547530
Издательство: Springer
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Цена: 74530.00 T
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Описание: It presents that potential effects of each independent variable on the dependent variable are not limited to direct and indirect effects. The path analysis shows each independent variable has a pure effect on the dependent variable. So, it can be shown the unique contribution of each independent variable to the variation of the dependent variable.

Автор: Daniels, Michael J.
Название: Bayesian nonparametrics for causal inference and missing data
ISBN: 036734100X ISBN-13(EAN): 9780367341008
Издательство: Taylor&Francis
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Цена: 100030.00 T
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Название: Sage handbook of regression analysis and causal inference
ISBN: 1446252442 ISBN-13(EAN): 9781446252444
Издательство: Sage Publications
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Цена: 142560.00 T
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Автор: Mark J. van der Laan; Sherri Rose
Название: Targeted Learning in Data Science
ISBN: 3319653032 ISBN-13(EAN): 9783319653037
Издательство: Springer
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Цена: 111790.00 T
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Описание: This textbook for graduate students in statistics, data science, and public health deals with the practical challenges that come with big, complex, and dynamic data.

Автор: Ding, Peng
Название: A First Course in Causal Inference
ISBN: 1032758627 ISBN-13(EAN): 9781032758626
Издательство: Taylor&Francis
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Цена: 66340.00 T
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Автор: Fang, Yixin
Название: Causal Inference in Pharmaceutical Statistics
ISBN: 1032560142 ISBN-13(EAN): 9781032560144
Издательство: Taylor&Francis
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Цена: 100030.00 T
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Автор: Humphreys, Macartan (wissenschaftszentrum Berlin Fur Sozialforschung) Jacobs, Alan M. (university Of British Columbia, Vancouver)
Название: Integrated inferences
ISBN: 1316620662 ISBN-13(EAN): 9781316620663
Издательство: Cambridge Academ
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Цена: 31670.00 T
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Описание: There is a growing consensus in the social sciences on the virtues of research strategies that combine quantitative with qualitative tools of inference. Integrated Inferences develops a framework for using causal models and Bayesian updating for qualitative and mixed-methods research. By making, updating, and querying causal models, researchers are able to integrate information from different data sources while connecting theory and empirics in a far more systematic and transparent manner than standard qualitative and quantitative approaches allow. This book provides an introduction to fundamental principles of causal inference and Bayesian updating and shows how these tools can be used to implement and justify inferences using within-case (process tracing) evidence, correlational patterns across many cases, or a mix of the two. The authors also demonstrate how causal models can guide research design, informing choices about which cases, observations, and mixes of methods will be most useful for addressing any given question.

Автор: Federica Russo
Название: Causality and Causal Modelling in the Social Sciences
ISBN: 9048179963 ISBN-13(EAN): 9789048179961
Издательство: Springer
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Цена: 139750.00 T
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Описание: This investigation into causal modelling presents the rationale of causality; i.e. what guides reasoning in causal modeling. In contrast to the dominant paradigm, it argues that causal models are governed by a variation, rather than regularity or invariance.

Автор: Burgess, Stephen (mrc Biostatistics Unit, Cambridge, Uk) Thompson, Simon G. (department Of Public Health And Primary Care, University Of Cambridge, Uk
Название: Mendelian randomization
ISBN: 1032019514 ISBN-13(EAN): 9781032019512
Издательство: Taylor&Francis
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Цена: 68390.00 T
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Описание: Mendelian randomization (MR) uses genetic instrumental variables to make inferences about causal effects based on observational data. It, therefore, can be a reliable way of assessing the causal nature of risk factors, such as biomarkers, for a wide range of disease outcomes.